Age estimation was used in forensic anthropology to help in the identification of individual remains and living person. However, the estimation methods tend to be unique and applicable only to a certain population. This paper analyzed age estimation using twelve regression models carried out on X-ray images of the left hand taken from an Asian data set for subjects under the age of 19. All the nineteen bones of the left hand were measured using free image software and the statistical analysis were performed using SPSS. There are two methods to determine age in this study which are single bone method and all bones method. For single bone method, S-curve regression model was found to have the highest R-square value using second metacarpal for males, and third proximal phalanx for females. For age estimation using single bone, fifth metacarpal from males and fifth proximal phalanx from females can be used due to the lowest mean square error (MSE) value. To conclude, multiple linear regressions is the best techniques for age estimation in cases where all bones are available, but if not, S-curve regression can be used using single bone method.
Growth and development rates may result from genetic programming of intrinsic processes that yield correlated rates between life stages. These intrinsic rates are thought to affect adult mortality probability and longevity. However, if proximate extrinsic factors (e.g., temperature, food) influence development rates differently between stages and yield low covariance between stages, then development rates may not explain adult mortality probability. We examined these issues based on study of 90 songbird species on four continents to capture the diverse life-history strategies observed across geographic space. The length of the embryonic period explained little variation (ca. 13%) in nestling periods and growth rates among species. This low covariance suggests that the relative importance of intrinsic and extrinsic influences on growth and development rates differs between stages. Consequently, nestling period durations and nestling growth rates were not related to annual adult mortality probability among diverse songbird species within or among sites. The absence of a clear effect of faster growth on adult mortality when examined in an evolutionary framework across species may indicate that species that evolve faster growth also evolve physiological mechanisms for ameliorating costs on adult mortality. Instead, adult mortality rates of species in the wild may be determined more strongly by extrinsic environmental causes.
The job satisfaction of academics is related to a number of variables of complex function such as demographic characters, the work itself, pay, work responsibilities, variety of tasks, promotional opportunities, relationship with co-workers and others. Academics may be simultaneously satisfied with some facets of the job and dissatisfied with others. This paper aims at determining the influential factors that contribute to the enhancement or reduction of academics' job satisfaction among private universities in Bangladesh with special reference to Dhaka, the capital city of Bangladesh. A total of 346 respondents are considered from ten private universities using non-probability sampling. A pre-tested and closed-ended questionnaire using a seven-point Likert scale is used for data collection. In this study, descriptive statistics, Pearson product moment correlation, multiple regression, and factor analysis are exercised as statistical tools. A conceptual model of job satisfaction is developed and applied for academics' job satisfaction. The results reveal that compensation package, supervisory support, job security, training and development opportunities, team cohesion, career growth, working conditions, and organizational culture and policies are positively associated with the academics' job satisfaction. Amongst them, three factors stood out as significant contributors for job satisfaction of academics i.e. compensation package, job security, and working conditions. Therefore, the management of private universities should focus their effort on these areas of human resource management for maintaining academics' job satisfaction and employee retention. The study will be useful for university management in improving overall job satisfaction as it suggests some strategies for employee satisfaction practices.
Level crossings are amongst the most complex of road safety issues, due to the addition of rail infrastructure, trains and train operations. The differences in the operational characteristics of different warning devices together with varying crossing, traffic or/and train characteristics, cause different driver behaviour at crossings. This paper compares driver behaviour towards two novel warning devices (rumble strips and in-vehicle audio warning) with two conventional warning devices (flashing light and stop sign) at railway level crossings using microsimulation modelling. Two safety performance indicators directly related to collision risks, violation and time-to-collision, were adopted. Results indicated the active systems were more effective at reducing likely collisions compared to passive devices. With the combined application of driving simulation and traffic microsimulation modelling, traffic safety performance indicators for a level crossing can be estimated. From these, relative safety comparisons for the different traffic devices are derived, or even for absolute safety evaluation with proper calibration from field investigations.
Segmentation and counting of blood cells are considered as an important step that helps to extract features to diagnose some specific diseases like malaria or leukemia. The manual counting of white blood cells (WBCs) and red blood cells (RBCs) in microscopic images is an extremely tedious, time consuming, and inaccurate process. Automatic analysis will allow hematologist experts to perform faster and more accurately. The proposed method uses an iterative structured circle detection algorithm for the segmentation and counting of WBCs and RBCs. The separation of WBCs from RBCs was achieved by thresholding, and specific preprocessing steps were developed for each cell type. Counting was performed for each image using the proposed method based on modified circle detection, which automatically counted the cells. Several modifications were made to the basic (RCD) algorithm to solve the initialization problem, detecting irregular circles (cells), selecting the optimal circle from the candidate circles, determining the number of iterations in a fully dynamic way to enhance algorithm detection, and running time. The validation method used to determine segmentation accuracy was a quantitative analysis that included Precision, Recall, and F-measurement tests. The average accuracy of the proposed method was 95.3% for RBCs and 98.4% for WBCs.
The increase in the number of fatalities caused by road accidents involving heavy vehicles every year has raised the level of concern and awareness on road safety in developing countries like Malaysia. Changes in the vehicle dynamic characteristics such as gross vehicle weight, travel speed, and vehicle classification will affect a heavy vehicle's braking performance and its ability to stop safely in emergency situations. As such, the aim of this study is to establish a more realistic new distance-based safety indicator called the minimum safe distance gap (MSDG), which incorporates vehicle classification (VC), speed, and gross vehicle weight (GVW).
This study aimed: i) to examine the relationship between the magnitude of cross-talk in mechanomyographic (MMG) signals generated by the extensor digitorum (ED), extensor carpi ulnaris (ECU), and flexor carpi ulnaris (FCU) muscles with the sub-maximal to maximal isometric grip force, and with the anthropometric parameters of the forearm, and ii) to quantify the distribution of the cross-talk in the MMG signal to determine if it appears due to the signal component of intramuscular pressure waves produced by the muscle fibers geometrical changes or due to the limb tremor.
Estimation of stature is an important step in developing a biological profile for human identification. It may provide a valuable indicator for an unknown individual in a population. The aim of this study was to analyse the relationship between stature and lower limb dimensions in the Malaysian population. The sample comprised 100 corpses, which included 69 males and 31 females between the age range of 20-90 years old. The parameters measured were stature, thigh length, lower leg length, leg length, foot length, foot height and foot breadth. Results showed that the mean values in males were significantly higher than those in females (p
The aim of the study was to compare the frequency and type of sleep disturbances in a group of Malaysian children aged 4 to 18 years with cerebral palsy (CP) with their nearest-age, able-bodied siblings and to identify factors associated with sleep disturbances.
Precise estimation of root biomass is important for understanding carbon stocks and dynamics in forests. Traditionally, biomass estimates are based on allometric scaling relationships between stem diameter and coarse root biomass calculated using linear regression (LR) on log-transformed data. Recently, it has been suggested that nonlinear regression (NLR) is a preferable fitting method for scaling relationships. But while this claim has been contested on both theoretical and empirical grounds, and statistical methods have been developed to aid in choosing between the two methods in particular cases, few studies have examined the ramifications of erroneously applying NLR. Here, we use direct measurements of 159 trees belonging to three locally dominant species in east China to compare the LR and NLR models of diameter-root biomass allometry. We then contrast model predictions by estimating stand coarse root biomass based on census data from the nearby 24-ha Gutianshan forest plot and by testing the ability of the models to predict known root biomass values measured on multiple tropical species at the Pasoh Forest Reserve in Malaysia. Based on likelihood estimates for model error distributions, as well as the accuracy of extrapolative predictions, we find that LR on log-transformed data is superior to NLR for fitting diameter-root biomass scaling models. More importantly, inappropriately using NLR leads to grossly inaccurate stand biomass estimates, especially for stands dominated by smaller trees.
Estimation of age from microscopic examination of human bone utilizes bone remodeling. This allows 2 regression equation to be determined in a specific population based on the variation in osteon turnover in different populations. The aim of this study was to provide age estimation for Malaysian males. Ground undecalcified cross sections were prepared from long limb bones of 50 deceased males aged between 21 and 78 years. Ten microstructural parameters were measured and subjected to multivariate regression analysis. Results showed that osteon count had the highest correlation with age (R = 0.43), and age was estimated to be within 10.94 years of the true value in 98% of males. Cross validation of the equation on 50 individuals showed close correspondence of true ages with estimated ages. Further studies are needed to validate and expand these results.
Youth–adult partnership (Y–AP) has emerged as a key practice for enacting two features of effective developmental settings: supportive adult relationships and support for efficacy and mattering. Previous studies have shown that when youth, supported by adults, actively participate in organizational and community decision making they are likely to show greater confidence and agency, empowerment and critical consciousness, and community connections. Most of the extant research on Y–AP is limited to qualitative studies and the identification of organizational best practices. Almost all research focuses on Western sociocultural settings. To address these gaps, 299 youth, age 15 to 24, were sampled from established afterschool and community programs in Malaysia to explore the contribution of Y–AP (operationalized as having two components: youth voice in decision-making and supportive adult relationships) to empowerment, agency and community connections. As hypothesized, hierarchical regressions indicated that program quality (Y–AP, safe environment and program engagement) contributed to agency, empowerment and community connections beyond the contribution of family, school and religion. Additionally, the Y–AP measures contributed substantially more variance than the other measures of program quality on each outcome. Interaction effects indicated differences by age for empowerment and agency but not for community connections. The primary findings in this inquiry replicate those found in previous interview and observational-oriented studies. The data suggests fertile ground for future research while demonstrating that Y–AP may be an effective practice for positive youth development outside of Western settings.
The main objective of this paper was to determine the utility of various anthropometric measures to assess total and regional body fatness using dual-energy X-ray absorptiometry (DXA) as the criterion in 454 adolescent boys and girls aged 12-19 years. Multivariable regression analyses of gender-specific and gender-combined models were used to determine anthropometric measures on DXA-derived body fatness models, after adjusting for known confounding biological factors. Partial correlation analyses, after adjusting for age, pubertal growth status and ethnicity in boys and girls, showed that body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), and waist-height ratio (WhtR) were significantly correlated with total body fat (TBF), percent body fat (%BF), android region fat (ARF) and trunk fat (TF) (all p<0.0001). BMI was the greatest independent determinant, contributing 43.8%-80.9% of the total variance for DXA-derived body fatness models. Results confirmed that a simple anthropometric index such as the BMI is a good surrogate indicator of body fat levels in Malay and Chinese adolescents.
Mixotrophic metabolism was evaluated as an option to augment the growth and lipid production of marine microalga Tetraselmis sp. FTC 209. In this study, a five-level three-factor central composite design (CCD) was implemented in order to enrich the W-30 algal growth medium. Response surface methodology (RSM) was employed to model the effect of three medium variables, that is, glucose (organic C source), NaNO3 (primary N source), and yeast extract (supplementary N, amino acids, and vitamins) on biomass concentration, X(max), and lipid yield, P(max)/X(max). RSM capability was also weighed against an artificial neural network (ANN) approach for predicting a composition that would result in maximum lipid productivity, Pr(lipid). A quadratic regression from RSM and a Levenberg-Marquardt trained ANN network composed of 10 hidden neurons eventually produced comparable results, albeit ANN formulation was observed to yield higher values of response outputs. Finalized glucose (24.05 g/L), NaNO3 (4.70 g/L), and yeast extract (0.93 g/L) concentration, affected an increase of X(max) to 12.38 g/L and lipid a accumulation of 195.77 mg/g dcw. This contributed to a lipid productivity of 173.11 mg/L per day in the course of two-week cultivation.
Crimes forecasting is an important area in the field of criminology. Linear models, such as regression and econometric models, are commonly applied in crime forecasting. However, in real crimes data, it is common that the data consists of both linear and nonlinear components. A single model may not be sufficient to identify all the characteristics of the data. The purpose of this study is to introduce a hybrid model that combines support vector regression (SVR) and autoregressive integrated moving average (ARIMA) to be applied in crime rates forecasting. SVR is very robust with small training data and high-dimensional problem. Meanwhile, ARIMA has the ability to model several types of time series. However, the accuracy of the SVR model depends on values of its parameters, while ARIMA is not robust to be applied to small data sets. Therefore, to overcome this problem, particle swarm optimization is used to estimate the parameters of the SVR and ARIMA models. The proposed hybrid model is used to forecast the property crime rates of the United State based on economic indicators. The experimental results show that the proposed hybrid model is able to produce more accurate forecasting results as compared to the individual models.
Relationships between six calcifying plankton groups and pH are explored in a highly biologically productive and data-rich area of the central North Sea using time-series datasets. The long-term trends show that abundances of foraminiferans, coccolithophores, and echinoderm larvae have risen over the last few decades while the abundances of bivalves and pteropods have declined. Despite good coverage of pH data for the study area there is uncertainty over the quality of this historical dataset; pH appears to have been declining since the mid 1990s but there was no statistical connection between the abundance of the calcifying plankton and the pH trends. If there are any effects of pH on calcifying plankton in the North Sea they appear to be masked by the combined effects of other climatic (e.g. temperature), chemical (nutrient concentrations) and biotic (predation) drivers. Certain calcified plankton have proliferated in the central North Sea, and are tolerant of changes in pH that have occurred since the 1950s but bivalve larvae and pteropods have declined. An improved monitoring programme is required as ocean acidification may be occurring at a rate that will exceed the environmental niches of numerous planktonic taxa, testing their capacities for acclimation and genetic adaptation.
The synthesis of fatty acid ethyl esters (FAEEs) by a two-step in situ (reactive) esterification/transesterification from Jatropha curcas L. (JCL) seeds using microwave system has been investigated. Free fatty acid was reduced from 14% to less than 1% in the first step using H2SO4 as acid catalyst after 35 min of microwave irradiation heating. The organic phase in the first step was subjected to a second reaction by adding 5 N KOH in ethanol as the basic catalyst. Response surface methodology (RSM) based on central composite design (CCD) was utilized to design the experiments and analyze the influence of process variables (particles seed size, time of irradiation, agitation speed and catalyst loading) on conversion of triglycerides (TGs) in the second step. The highest triglycerides conversion to fatty acid ethyl esters (FAEEs) was 97.29% at the optimum conditions:<0.5mm seed size, 12.21 min irradiation time, 8.15 ml KOH catalyst loading and 331.52 rpm agitation speed in the 110 W microwave power system.
Candlenut oil was extracted using supercritical CO(2) (SC-CO(2)) with an optimization of parameters, by the response surface methodology. The ground candlenut samples were treated in 2 different ways, that is, dried in either a heat oven (sample moisture content of 2.91%) or dried in a vacuum oven (sample moisture content of 1.98%), before extraction. An untreated sample (moisture content of 4.87%) was used as a control. The maximum percentage of oil was extracted from the heat-oven-dried sample (77.27%), followed by the vacuum-oven-dried sample (74.32%), and the untreated sample (70.12%). At an SC-CO(2) pressure of 48.26 Mpa and 60 min of extraction time, the optimal temperatures for extraction were found to be 76.4 °C, 73.9 °C, and 70.6 °C for the untreated, heat-oven-dried, and vacuum-oven-dried samples, respectively. The heat-oven-dried sample contains the highest percentage of linoleic acid, followed by the untreated and vacuum-oven-dried samples. The antiradical activity of candlenut oil corresponded to an IC(50) value of 30.37 mg/mL.
This study aimed to identify the significant factors that give large effects on the efficiency of Cu(II) extraction from aqueous solutions by soybean oil-based organic solvents using fractional factorial design. Six factors (mixing time (t), di-2-ethylhexylphosphoric acid concentration ([D2EHPA]), organic to aqueous phase ratio (O:A), sodium sulfate concentration ([Na(2)SO(4)]), equilibrium pH (pH(eq)) and tributylphosphate concentration ([TBP])) affecting the percentage extraction (%E) of Cu(II) were investigated. A 2(6-1) fractional factorial design was applied and the results were analyzed statistically. The results show that only [D2EHPA], pH(eq) and their second-order interaction ([D2EHPA] × pH(eq)) influenced the %E significantly. Regression models for %E were developed and the adequacy of the reduced model was examined. The results of this study indicate that fractional factorial design is a useful tool for screening a large number of variables and reducing the number of experiments.